






import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict




@pytest.mark.parametrize(
    """files"""   ,      [
        ["""full:README.md""", """dataset_infos.json"""],
        ["""empty:README.md""", """dataset_infos.json"""],
        ["""dataset_infos.json"""],
        ["""full:README.md"""],
    ]   ,      )
def       _SCREAMING_SNAKE_CASE (							__snake_case   ,      __snake_case )				->						List[str]:
       _UpperCAmelCase							=    tmp_path_factory.mktemp("""dset_infos_dir""" )
       if "full:README.md" in files:
              with open(dataset_infos_dir / """README.md"""   ,      """w""" ) as f:
                     f.write("""---\ndataset_info:\n  dataset_size: 42\n---""" )
       if "empty:README.md" in files:
              with open(dataset_infos_dir / """README.md"""   ,      """w""" ) as f:
                     f.write("""""" )
    # we want to support dataset_infos.json for backward compatibility
       if "dataset_infos.json" in files:
              with open(dataset_infos_dir / """dataset_infos.json"""   ,      """w""" ) as f:
                     f.write("""{\"default\": {\"dataset_size\": 42}}""" )
       _UpperCAmelCase							=    DatasetInfosDict.from_directory(__snake_case )
       assert dataset_infos
       assert dataset_infos["default"].dataset_size == 4_2




@pytest.mark.parametrize(
    """dataset_info"""   ,      [
        DatasetInfo(),
        DatasetInfo(
            description="""foo"""   ,      features=Features({"""a""": Value("""int32""" )} )   ,      builder_name="""builder"""   ,      config_name="""config"""   ,      version="""1.0.0"""   ,      splits=[{"""name""": """train"""}]   ,      download_size=4_2   ,      ),
    ]   ,      )
def       _SCREAMING_SNAKE_CASE (							__snake_case   ,      __snake_case )				->						Optional[int]:
       _UpperCAmelCase							=    str(__snake_case )
       dataset_info.write_to_directory(__snake_case )
       _UpperCAmelCase							=    DatasetInfo.from_directory(__snake_case )
       assert dataset_info == reloaded
       assert os.path.exists(os.path.join(__snake_case   ,      """dataset_info.json""" ) )




def       _SCREAMING_SNAKE_CASE (							)				->						Any:
       _UpperCAmelCase							=    DatasetInfo(
           description="""foo"""   ,      citation="""bar"""   ,      homepage="""https://foo.bar"""   ,      license="""CC0"""   ,      features=Features({"""a""": Value("""int32""" )} )   ,      post_processed={}   ,      supervised_keys=()   ,      task_templates=[]   ,      builder_name="""builder"""   ,      config_name="""config"""   ,      version="""1.0.0"""   ,      splits=[{"""name""": """train""", """num_examples""": 4_2}]   ,      download_checksums={}   ,      download_size=1_3_3_7   ,      post_processing_size=4_4_2   ,      dataset_size=1_2_3_4   ,      size_in_bytes=1_3_3_7 + 4_4_2 + 1_2_3_4   ,      )
       _UpperCAmelCase							=    dataset_info._to_yaml_dict()
       assert sorted(__snake_case ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML )
       for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
              assert key in dataset_info_yaml_dict
              assert isinstance(dataset_info_yaml_dict[key]   ,      (list, dict, int, str) )
       _UpperCAmelCase							=    yaml.safe_dump(__snake_case )
       _UpperCAmelCase							=    yaml.safe_load(__snake_case )
       assert dataset_info_yaml_dict == reloaded




def       _SCREAMING_SNAKE_CASE (							)				->						int:
       _UpperCAmelCase							=    DatasetInfo()
       _UpperCAmelCase							=    dataset_info._to_yaml_dict()
       assert dataset_info_yaml_dict == {}





@pytest.mark.parametrize(
    """dataset_infos_dict"""   ,      [
        DatasetInfosDict(),
        DatasetInfosDict({"""default""": DatasetInfo()} ),
        DatasetInfosDict({"""my_config_name""": DatasetInfo()} ),
        DatasetInfosDict(
            {
                """default""": DatasetInfo(
                    description="""foo"""   ,      features=Features({"""a""": Value("""int32""" )} )   ,      builder_name="""builder"""   ,      config_name="""config"""   ,      version="""1.0.0"""   ,      splits=[{"""name""": """train"""}]   ,      download_size=4_2   ,      )
            } ),
        DatasetInfosDict(
            {
                """v1""": DatasetInfo(dataset_size=4_2 ),
                """v2""": DatasetInfo(dataset_size=1_3_3_7 ),
            } ),
    ]   ,      )
def       _SCREAMING_SNAKE_CASE (							__snake_case   ,      __snake_case )				->						Union[str, Any]:
       _UpperCAmelCase							=    str(__snake_case )
       dataset_infos_dict.write_to_directory(__snake_case )
       _UpperCAmelCase							=    DatasetInfosDict.from_directory(__snake_case )

       # the config_name of the dataset_infos_dict take over the attribute
       for config_name, dataset_info in dataset_infos_dict.items():
              _UpperCAmelCase							=    config_name
              # the yaml representation doesn't include fields like description or citation
              # so we just test that we can recover what we can from the yaml
              _UpperCAmelCase							=    DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict() )
       assert dataset_infos_dict == reloaded

       if dataset_infos_dict:
              assert os.path.exists(os.path.join(__snake_case   ,      """README.md""" ) )

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_    :			Any    =	logging.get_logger(__name__)

lowerCamelCase_    :			Dict    =	{
    """facebook/dpr-ctx_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-ctx_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-multiset-base""": (
        """https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"""
    ),
}

class 							_UpperCamelCase					(       _A	):






			'''simple docstring'''

			__UpperCamelCase   :    Any          =			"""dpr"""

			def __init__(							self			:							str    ,						snake_case_			:							Any=3_0522    ,						snake_case_			:							List[str]=768    ,						snake_case_			:							List[str]=12    ,						snake_case_			:							Union[str, Any]=12    ,						snake_case_			:							Tuple=3072    ,						snake_case_			:							Any="gelu"    ,						snake_case_			:							Optional[Any]=0.1    ,						snake_case_			:							str=0.1    ,						snake_case_			:							Dict=512    ,						snake_case_			:							int=2    ,						snake_case_			:							Union[str, Any]=0.02    ,						snake_case_			:							str=1e-12    ,						snake_case_			:							List[str]=0    ,						snake_case_			:							Any="absolute"    ,						snake_case_			:							int = 0    ,						**snake_case_			:							int    ,						):
							super().__init__(pad_token_id=snake_case_    ,						**snake_case_   )

							UpperCamelCase_:				str						=    vocab_size
							UpperCamelCase_:				Optional[int]						=    hidden_size
							UpperCamelCase_:				int						=    num_hidden_layers
							UpperCamelCase_:				Any						=    num_attention_heads
							UpperCamelCase_:				int						=    hidden_act
							UpperCamelCase_:				Optional[Any]						=    intermediate_size
							UpperCamelCase_:				Tuple						=    hidden_dropout_prob
							UpperCamelCase_:				Tuple						=    attention_probs_dropout_prob
							UpperCamelCase_:				str						=    max_position_embeddings
							UpperCamelCase_:				Any						=    type_vocab_size
							UpperCamelCase_:				Tuple						=    initializer_range
							UpperCamelCase_:				List[Any]						=    layer_norm_eps
							UpperCamelCase_:				Tuple						=    projection_dim
							UpperCamelCase_:				Dict						=    position_embedding_type






